feat: add accessor protocol and refactor stats/base/nanmskmax

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Author: rahulptl165

lib/node_modules/@stdlib/stats/base/nanmskmax/README.md

@@ -44,28 +44,25 @@ Computes the maximum value of a strided array `x` according to a `mask`, ignorin
 var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];
 var mask = [ 0, 0, 1, 0, 0 ];
 
-var v = nanmskmax( x.length, x, 1, mask, 1 );
+var v = nanmskmax( 5, x, 1, mask, 1 );
 // returns 2.0
 ```
 
 The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 -   **mask**: mask [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation.
--   **strideMask**: index increment for `mask`.
+-   **strideMask**: stride length for `mask`.
 
-The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the maximum value of every other element in `x`,
+The `N` and stride parameters determine which elements int the strided arrays are accessed at runtime. For example, to compute the maximum value of every other element in `x`,
 
 ```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
 var x = [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ];
 var mask = [ 0, 0, 0, 0, 0, 0, 1, 1 ];
-var N = floor( x.length / 2 );
 
-var v = nanmskmax( N, x, 2, mask, 2 );
+var v = nanmskmax( 4, x, 2, mask, 2 );
 // returns 4.0
 ```
 
@@ -76,17 +73,14 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
 var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
 var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = nanmskmax( N, x1, 2, mask1, 2 );
+var v = nanmskmax( 4, x1, 2, mask1, 2 );
 // returns 4.0
 ```
 
@@ -98,7 +92,7 @@ Computes the maximum value of a strided array according to a `mask`, ignoring `N
 var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];
 var mask = [ 0, 0, 1, 0, 0 ];
 
-var v = nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 );
+var v = nanmskmax.ndarray( 5, x, 1, 0, mask, 1, 0 );
 // returns 2.0
 ```
 
@@ -107,16 +101,13 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetMask**: starting index for `mask`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the maximum value for every other value in `x` starting from the second value
 
 ```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
-var x = [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ];
-var mask = [ 0, 0, 0, 0, 0, 0, 1, 1 ];
-var N = floor( x.length / 2 );
+var x = [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0, NaN, NaN ];
+var mask = [ 0, 0, 0, 0, 0, 0, 1, 1, 0, 0 ];
 
-var v = nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 );
+var v = nanmskmax.ndarray( 5, x, 2, 1, mask, 2, 1 );
 // returns 4.0
 ```
 
@@ -130,6 +121,7 @@ var v = nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 );
 
 -   If `N <= 0`, both functions return `NaN`.
 -   Depending on the environment, the typed versions ([`dnanmskmax`][@stdlib/stats/base/dnanmskmax], [`snanmskmax`][@stdlib/stats/base/snanmskmax], etc.) are likely to be significantly more performant.
+-   Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]).
 
 </section>
 
@@ -142,31 +134,18 @@ var v = nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var nanmskmax = require( '@stdlib/stats/base/nanmskmax' );
 
-var mask;
-var x;
-var i;
-
-x = new Float64Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-    if ( randu() < 0.2 ) {
-        mask[ i ] = 1;
-    } else {
-        mask[ i ] = 0;
-    }
-    if ( randu() < 0.1 ) {
-        x[ i ] = NaN;
-    } else {
-        x[ i ] = round( (randu()*100.0) - 50.0 );
-    }
-}
+var x = uniform( 10, -50.0, 50.0, {
+    'dtype': 'float64'
+});
 console.log( x );
+
+var mask = bernoulli( x.length, 0.2, {
+    'dtype': 'uint8'
+});
 console.log( mask );
 
 var v = nanmskmax( x.length, x, 1, mask, 1 );
@@ -215,6 +194,8 @@ console.log( v );
 
 [@stdlib/stats/base/snanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/snanmskmax
 
+[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
+
 <!-- </related-links> -->
 
 </section>

lib/node_modules/@stdlib/stats/base/nanmskmax/benchmark/benchmark.js

@@ -21,13 +21,21 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
 var nanmskmax = require( './../lib/nanmskmax.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'generic'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,20 +46,8 @@ var nanmskmax = require( './../lib/nanmskmax.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = [];
-	mask = [];
-	for ( i = 0; i < len; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask.push( 1 );
-		} else {
-			mask.push( 0 );
-		}
-		x.push( ( randu()*20.0 ) - 10.0 );
-	}
+	var mask = bernoulli( len, 0.2, options );
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/nanmskmax/benchmark/benchmark.ndarray.js

@@ -21,13 +21,21 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
 var nanmskmax = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'generic'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,20 +46,8 @@ var nanmskmax = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = [];
-	mask = [];
-	for ( i = 0; i < len; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask.push( 1 );
-		} else {
-			mask.push( 0 );
-		}
-		x.push( ( randu()*20.0 ) - 10.0 );
-	}
+	var mask = bernoulli( len, 0.2, options );
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/nanmskmax/docs/repl.txt

@@ -3,8 +3,8 @@
     Computes the maximum value of a strided array according to a mask and
     ignoring `NaN` values.
 
-    The `N` and `stride` parameters determine which elements are accessed at
-    runtime.
+    The `N` and stride parameters determine which elements in the strided arrays
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce offsets, use a typed
     array views.
@@ -26,13 +26,13 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride length for `x`.
 
     mask: Array<number>|TypedArray
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride length for `mask`.
 
     Returns
     -------
@@ -47,22 +47,21 @@
     > {{alias}}( x.length, x, 1, mask, 1 )
     2.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];
     > mask = [ 0, 0, 0, 0, 0, 0, 1 ];
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, x, 2, mask, 2 )
+    > {{alias}}( 3, x, 2, mask, 2 )
     2.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
     > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, x1, 2, mask1, 2 )
+    > {{alias}}( 3, x1, 2, mask1, 2 )
     2.0
 
+
 {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
     Computes the maximum value of a strided array according to a mask,
     ignoring `NaN` values and using alternative indexing semantics.
@@ -80,7 +79,7 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride length for `x`.
 
     offsetX: integer
         Starting index for `x`.
@@ -89,7 +88,7 @@
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride length for `mask`.
 
     offsetMask: integer
         Starting index for `mask`.
@@ -104,14 +103,13 @@
     // Standard Usage:
     > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];
     > var mask = [ 0, 0, 0, 1, 0 ];
-    > {{alias}}.ndarray( x.length, x, 1, 0, mask, 1, 0 )
+    > {{alias}}.ndarray( 5, x, 1, 0, mask, 1, 0 )
     2.0
 
     // Using offset parameter:
     > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];
     > mask = [ 0, 0, 0, 0, 0, 0, 1 ];
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 )
     2.0
 
     See Also

lib/node_modules/@stdlib/stats/base/nanmskmax/docs/types/index.d.ts

@@ -20,7 +20,12 @@
 
 /// <reference types="@stdlib/types"/>
 
-import { NumericArray } from '@stdlib/types/array';
+import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array';
+
+/**
+* Input array.
+*/
+type InputArray = NumericArray | Collection<number> | AccessorArrayLike<number>;
 
 /**
 * Interface describing `nanmskmax`.
@@ -31,9 +36,9 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param strideX - `x` stride length
+	* @param strideX - stride length for `x`
 	* @param mask - mask array
-	* @param strideMask - `mask` stride length
+	* @param strideMask - stride length for `mask`
 	* @returns maximum value
 	*
 	* @example
@@ -43,17 +48,17 @@ interface Routine {
 	* var v = nanmskmax( x.length, x, 1, mask, 1 );
 	* // returns 2.0
 	*/
-	( N: number, x: NumericArray, strideX: number, mask: NumericArray, strideMask: number ): number;
+	( N: number, x: InputArray, strideX: number, mask: InputArray, strideMask: number ): number;
 
 	/**
 	* Computes the maximum value of a strided array according to a mask, ignoring `NaN` values and using alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param strideX - `x` stride length
+	* @param strideX - stride length for `x`
 	* @param offsetX - `x` starting index
 	* @param mask - mask array
-	* @param strideMask - `mask` stride length
+	* @param strideMask - stride length for `mask`
 	* @param offsetMask - `mask` starting index
 	* @returns maximum value
 	*
@@ -64,17 +69,17 @@ interface Routine {
 	* var v = nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 );
 	* // returns 2.0
 	*/
-	ndarray( N: number, x: NumericArray, strideX: number, offsetX: number, mask: NumericArray, strideMask: number, offsetMask: number ): number;
+	ndarray( N: number, x: InputArray, strideX: number, offsetX: number, mask: InputArray, strideMask: number, offsetMask: number ): number;
 }
 
 /**
 * Computes the maximum value of a strided array according to a mask, ignoring `NaN` values.
 *
 * @param N - number of indexed elements
 * @param x - input array
-* @param strideX - `x` stride length
+* @param strideX - stride length for `x`
 * @param mask - mask array
-* @param strideMask - `mask` stride length
+* @param strideMask - stride length for `mask`
 * @returns maximum value
 *
 * @example